Machine Learning Scientist, Pricing/Personalization (Open to Remote) in London
Machine Learning Scientist, Pricing/Personalization (Open to Remote)

Machine Learning Scientist, Pricing/Personalization (Open to Remote) in London

London Full-Time 90000 - 123000 £ / year (est.) Home office possible
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At a Glance

  • Tasks: Build and improve machine learning products for book pricing and recommendations.
  • Company: Join Penguin Random House, a leading publishing house embracing AI and innovation.
  • Benefits: Enjoy competitive salary, comprehensive benefits, and generous paid time off.
  • Why this job: Make an impact in the world of books using cutting-edge machine learning technology.
  • Qualifications: Master's or PhD in a quantitative field with strong Python and SQL skills.
  • Other info: Remote work options available; dynamic team with excellent career growth opportunities.

The predicted salary is between 90000 - 123000 £ per year.

The Data Science team at Penguin Random House is seeking two Machine Learning Scientists to build and improve machine learning products that power how we understand demand, set strategy, and connect readers with books. We're hiring across both our recommendation and pricing teams. In this role, you will use rich datasets to build sophisticated models that either recommend books to readers or help price books for the market. Our recommendation systems drive discovery across our digital channels and marketing, while our pricing products model market response to optimize revenue and mitigate risks to sales and brands.

As the world's leading publishing house, Penguin Random House is AI-forward and continues to invest in modern machine learning to shape the future of book discovery, sales, and customer engagement. Our Data Science team applies ML across personalization, forecasting, pricing, and experimentation, and we actively explore emerging AI capabilities when they can meaningfully improve customer experiences.

This role spans the ML lifecycle; from problem framing and prototyping to production and iteration, with a strong emphasis on writing robust, maintainable software and using modern AI tools thoughtfully to accelerate development.

Specific responsibilities:
  • Own the ML lifecycle: frames problems, prototypes solutions, validates performance, and iterates based on measurement and feedback.
  • Applies sound statistical and ML practices for feature development, training, evaluation, validation, and maintenance.
  • Defines success metrics and uses offline evaluation plus online experimentation (including A/B tests) to validate performance, monitor quality over time, and drive ongoing iteration.
  • Partners with engineering and platform counterparts to productionize models, including repeatable training, deployment workflows, monitoring, and refresh strategies.
  • Diagnoses model performance issues and data quality problems; communicates findings and recommended actions clearly to stakeholders.
  • Writes maintainable, production-minded code and contributes to team standards (code review, documentation, reproducibility, and testing where appropriate).
  • Stays current on applied ML and uses modern AI tools to accelerate exploration, questioning, and implementation without sacrificing quality.
Please apply if you meet the following qualifications:
  • Master's with 2+ years of applied work experience OR PhD in Computer Science, Machine Learning, Engineering, Operations Research, Statistics or a related quantitative field.
  • Strong proficiency in Python and common ML frameworks and libraries (for example PyTorch or TensorFlow).
  • Strong SQL skills and experience working with large datasets for feature development, analysis, and validation.
  • Experience taking models from development to production (batch scoring, APIs, or downstream integration).
  • Solid understanding of experimentation and measurement.
  • Being cutting edge. Use the latest AI tools to develop well-designed and robust software.
  • Strong communication skills and ability to translate between business goals and technical solutions.
  • Familiarity with cloud and modern data/ML tooling (AWS, Databricks, Docker, Kubernetes, Spark, or similar).
  • Exposure to MLOps concepts and tooling (model registries, pipelines, monitoring, reproducibility).
Preferred qualifications:
  • Forecasting: Experience with time series forecasting, causal/market-response modeling, optimization, or risk-aware modeling.
  • Familiarity with automated model retraining, monitoring, and long-running model maintenance.
  • Personalization: Experience with recommender systems, ranking/retrieval, personalization, segmentation, propensity modeling, or targeting.
  • Familiarity with experimentation, measurement, and online evaluation.

Please be advised that candidates selected to advance to the 1st round of interviews will be required to show photo ID on camera, and final interviews for this role will be in person at a Penguin Random House location.

The salary range for this position is $130,000 - $175,000. All positions are currently eligible for an annual profit award or bonus, subject to company results. Applications for this role will be accepted through February 10, 2026 or until the role is filled. We encourage you to apply early, as we review applications on a rolling basis. Please include your resume and cover letter for consideration.

Penguin Random House job postings include a good faith compensation range for each open position. The salary range listed is specific to each particular open position and takes into account various factors including the specifics of the individual role, and candidate's relevant experience and qualifications.

Full-time employees are eligible for our comprehensive benefits program. Our range of benefits include, but are not limited to, Medical/Prescription drug insurance, Dental, Vision, Health Care/Dependent Care Flexible Spending Account, Health Savings Account, Pre-Tax and Roth 401(k), Short and Long-Term Disability Insurance, Life/AD&D Insurance, Commuter Benefits, Student Loan Repayment Program, Educational Assistance & generous paid time off.

Penguin Random House is the leading adult and children's publishing house in North America, the United Kingdom and many other regions around the world. In publishing the best books in every genre and subject for all ages, we are committed to quality, excellence in execution, and innovation throughout the entire publishing process: editorial, design, marketing, publicity, sales, production, and distribution.

Penguin Random House values the array of talents and perspectives that a diverse workforce brings. All qualified applicants will receive consideration for employment without regard to race, national origin, religion, age, color, sex, sexual orientation, gender identity, disability, or protected veteran status.

Machine Learning Scientist, Pricing/Personalization (Open to Remote) in London employer: Knopf Doubleday Group

At Penguin Random House, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. Our commitment to employee growth is evident through comprehensive benefits, including generous paid time off and educational assistance, alongside the opportunity to work with cutting-edge machine learning technologies in a supportive environment. Join us in shaping the future of book discovery and customer engagement while enjoying the flexibility of remote work.
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Contact Detail:

Knopf Doubleday Group Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Machine Learning Scientist, Pricing/Personalization (Open to Remote) in London

✨Tip Number 1

Network like a pro! Reach out to folks in the industry, attend meetups, and connect with current employees at Penguin Random House. A friendly chat can sometimes lead to opportunities that aren’t even advertised!

✨Tip Number 2

Prepare for those interviews! Brush up on your machine learning concepts, especially around pricing and personalization. Be ready to discuss your past projects and how you’ve tackled challenges in the ML lifecycle.

✨Tip Number 3

Show off your coding skills! During technical interviews, be prepared to write code on the spot. Practice common algorithms and data structures in Python, and make sure you’re comfortable with ML frameworks like PyTorch or TensorFlow.

✨Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in joining the Penguin Random House team!

We think you need these skills to ace Machine Learning Scientist, Pricing/Personalization (Open to Remote) in London

Machine Learning
Python
SQL
Statistical Analysis
Model Development
Feature Engineering
A/B Testing
Data Quality Assessment
Cloud Computing
MLOps
Recommender Systems
Time Series Forecasting
Communication Skills
Experimentation
Software Development Best Practices

Some tips for your application 🫡

Tailor Your Application: Make sure to customise your resume and cover letter for the Machine Learning Scientist role. Highlight your experience with ML frameworks, Python, and any relevant projects that showcase your skills in pricing or personalisation.

Showcase Your Technical Skills: Don’t hold back on your technical prowess! Include specific examples of how you've used SQL, Python, and ML tools in past projects. This is your chance to shine and show us you can handle the data-heavy tasks we throw your way.

Be Clear and Concise: When writing your application, keep it clear and to the point. Use straightforward language to explain your experience and how it relates to the role. We appreciate a well-structured application that’s easy to read!

Apply Early!: We review applications on a rolling basis, so don’t wait until the last minute! Get your application in early through our website to increase your chances of standing out in the crowd.

How to prepare for a job interview at Knopf Doubleday Group

✨Know Your ML Lifecycle

Make sure you understand the entire machine learning lifecycle, from problem framing to production. Be ready to discuss how you've applied these stages in your previous work, especially in relation to pricing and recommendation systems.

✨Showcase Your Coding Skills

Since writing maintainable code is crucial for this role, be prepared to demonstrate your proficiency in Python and any relevant ML frameworks. Bring examples of your past projects where you’ve implemented robust software solutions.

✨Prepare for Technical Questions

Expect questions on statistical practices, feature development, and model evaluation. Brush up on your SQL skills and be ready to discuss how you've worked with large datasets to validate model performance.

✨Communicate Clearly

Strong communication skills are key. Practice explaining complex technical concepts in simple terms, as you'll need to translate between business goals and technical solutions during the interview.

Machine Learning Scientist, Pricing/Personalization (Open to Remote) in London
Knopf Doubleday Group
Location: London
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  • Machine Learning Scientist, Pricing/Personalization (Open to Remote) in London

    London
    Full-Time
    90000 - 123000 £ / year (est.)
  • K

    Knopf Doubleday Group

    50-100
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